Discussion Week 11
Instructions:
1. The objective of this activity is to exchange arrive at a consensus about the methodology and data analysis of several academic articles. Some of the articles are provided for the professor while other articles will be provided by each student.
2. In this peer discussion, you will start threads.
3. On Wednesday or Thursday before noon, as if you were posting in a blog, you need to post on Blackboard one of the articles that attached
4. In the post you will attach the full version of the article and will describe:
a) Research question or main research question.
b) Main goal of the research
c) The data collection, quantitative or qualitative.
d) The n=X. The number of participants/events/situations analyzed. [footnoteRef:1] [1: ]
e) Description of the participants/events/situations analyzed.
f) The data analysis used. Summarize the general idea of that data analysis and some of the steps of the data analysis process.
g) If so, what is the theoretical framework or model that the authors are using?
A systematic review of knowledge sharing challenges and practices in global software development
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International Journal of Information Management XXXXXXXXXX–1019
Contents lists available at ScienceDirect
International Journal of Information Management
jou rna l h om epage: www.elsev ier .com/ locate / i j in fomgt
systematic review of knowledge sharing challenges and practices in
lobal software development
ansooreh Zahedia,∗, Mojtaba Shahinb, Muhammad Ali Babarb
IT University of Copenhagen, Rued Langgaards Vej 7, 2300 Copenhagen, Denmark
The University of Adelaide, Adelaide, South Australia 5005, Australia
r t i c l e i n f o
rticle history:
eceived 6 July 2015
eceived in revised form 24 March 2016
ccepted 13 June 2016
vailable online 7 July 2016
eywords:
nowledge sharing
nowledge management (KM)
lobal software development (GSD)
ystematic literature review (SLR)
mpirical software engineering
a b s t r a c t
Context: Global Software Development (GSD) presents significant challenges to share and understand
knowledge required for developing software. Organizations are expected to implement appropriate
practices to address knowledge-sharing challenges in GSD. With the growing literature on GSD and
its widespread adoption, it is important to build a body of knowledge to support future research and
effective knowledge sharing practices.
Objective: We aimed at systematically identifying and synthesizing knowledge sharing challenges and
practices. We also intended to classify the recurrent challenges and most frequently reported practices
in different contextual settings.
Method: We used Systematic Literature Review (SLR) for reviewing 61 primary studies that were selected
after searching the GSD literature published over the last 14 years (2000–September XXXXXXXXXXWe applied
thematic analysis method for analysing the data extracted from the reviewed primary studies.
Results: Our findings revealed that knowledge sharing challenges and practices in GSD could be classi-
fied in 6 main themes: management, team structure, work processes/practices, team cognition, social
attributes and technology. In regard to contextual settings, we found empirical studies were mainly con-
ducted in an offshore outsourcing collaboration model distributed between two sites. Most of the studied
organizations were large enterprises. Many of the studies did not report any information for several con-
textual attributes that made it difficult to analyse the reported challenges and practices with respect to
their respective contexts.
Conclusion: We can conclude: (a) there is a higher tendency among researchers to report practices
than challenges of knowledge sharing in GSD. (b) Given our analysis, most of the reported knowledge
sharing challenges and practices fall under the theme of “work practices”. (c) The technology related
knowledge-sharing challenges are the least reported; we discussed the available technologies for sup-
porting knowledge sharing needs in GSD. (d) The organizational contextual information is missing from a
large number of studies; hence, it was not possible to investigate the potential relations between knowl-
edge sharing challenges/practices and the contextual attributes of GSD teams. We assert the need of
exploring knowledge sharing in the context of small/medium sized organizations to avoid the risk of
findings being biased by specific empirical setting (e.g., large enterprises distributed between US and
India).
© XXXXXXXXXXElsevier Ltd. All rights reserved.
. Introduction
Global Software Development (GSD) has become an established
oftware development paradigm that promises several advantages
ut also suffers from well-known limitations (Herbsleb et al., 2001;
∗ Corresponding author.
E-mail addresses: XXXXXXXXXX (M. Zahedi), XXXXXXXXXX
M. Shahin), XXXXXXXXXX (M. Ali Babar).
ttp://dx.doi.org/10.1016/j.ijinfomgt XXXXXXXXXX
XXXXXXXXXX/© 2016 Elsevier Ltd. All rights reserved.
Damian & Moitra, 2006; Bhat, Mayank, & Murthy, XXXXXXXXXXThe
promised benefits include enabling organizations to implement
strategies like Follow The Sun (FTS), benefiting from cost advan-
tages in certain parts of the world, being in close proximity to
customers, and creating opportunities for merger and acquisition,
and accessing a large pool of talented software developers (Damian
& Moitra, 2006; Herbsleb & Moitra, 2002; Grinter, Herbsleb, & Perry,
1999). GSD can also result in significantly increased complexity for
project teams, who may have to face several kinds of new chal-
lenges. Most of the GSD challenges stem from what is known as
dx.doi.org/10.1016/j.ijinfomgt XXXXXXXXXX
http://www.sciencedirect.com/science/journal/ XXXXXXXXXX
http://www.elsevier.com/locate/ijinfomgt
http://crossmark.crossref.org/dialog/?doi=10.1016/j.ijinfomgt XXXXXXXXXX&domain=pdf
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
mailto: XXXXXXXXXX
dx.doi.org/10.1016/j.ijinfomgt XXXXXXXXXX
9 Inform
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96 M. Zahedi et al. / International Journal of
SD distances, i.e., temporal, geographical, cultural, and linguistic
istances. These distances lead to communication, coordination,
nd collaboration challenges (Grinter et al., 1999; Ågerfalk et al.,
005; Carmel & Agarwal, 2001) that can impact several areas of
oftware development. One of the key areas of software develop-
ent being impacted by GSD is knowledge sharing as software
evelopment is a knowledge-intensive activity whose success is
argely dependent upon effective knowledge sharing among soft-
are development teams (Kotlarsky & Oshri, 2005; Khan, Niazi, &
hmad, XXXXXXXXXXGSD team members may find it difficult (or even
mpossible) to share both tacit and explicit knowledge within a
eam that is geographically distributed.
Knowledge sharing is an integral part of Knowledge Manage-
ent (KM) (Choo & de Alvarenga Neto, 2010; Santos, Goldman,
de Souza, XXXXXXXXXXIt is defined as « provision of task informa-
ion and know-how to a person, so that (s) he can collaborate with
thers to solve problems, develop new ideas or implement poli-
ies or procedures» (Santos et al., 2014; Cummings, XXXXXXXXXXChoo
nd Alvarenga (Choo & de Alvarenga Neto, 2010) identified four
ajor categories of conditions to enable knowledge sharing (Choo
de Alvarenga Neto, 2010): social/behavioral characteristics of
eams (e.g., mutual trust, attentive enquiry, open dialogues), cogni-
ive/epistemic attributes (e.g., common knowledge, shared values
nd goals), organizational structure/strategies (e.g. empowered
ivisions, leadership style) and provision of information systems
e.g., internet, intranet, yellow pages).
Ebert and De Man (Ebert & Man, 2008) discuss that effectively
anaging software engineering knowledge (i.e., project, product,
nd process) is of growing importance given the ever-changing
nvironments of software development, e.g., globalization. They
Ebert & Man, 2008) argued that in GSD settings, vendors usually
ossess technical expertise and knowledge about a project, while
lients hold requirements and application domain knowledge.
owever, vendors without proper understanding of require-
ents and application domain knowledge cannot effectively and
fficiently apply their technical skills; and clients could not appro-
riately provide business requirements without understanding
nowledge needs of vendors. Bjornson and Dingsøyr XXXXXXXXXXreport
hat KM in software engineering is mainly based on utilizing infor-
ation technologies.
Boden and colleagues (Boden et al., 2012) criticize the
mplementation of traditional KM approaches that tend to de-
ontextualize by codifying knowledge but neglect behavioral
spects and social learning that are specifically influential in GSD
eams. GSD impedes the opportunities for face-to-face interaction
nd informal chats between distributed team members (Grinter
t al., 1999; Ågerfalk et al., 2005) which are considered quite help-
ul for sharing knowledge (Grinter et al., 1999; Noll, Beecham, &
ichardson, XXXXXXXXXXTime zone differences also decrease the mech-
nisms of ad-hoc knowledge sharing by answering on-the-spot
uestions. Cultural and linguistic distance plays a significant role
n communication gaps between distant colleagues. From socio-
ehavioural perspectives, several studies (e.g., Kotlarsky & Oshri,
005; Hinds & McGrath, 2006) indicate that developing trust and
apport between dispersed members facilitate knowledge shar-
ng.